Robust and Vector Quantization.
Abstract
In this report, the authors consider the quantization of random sources. The problem of signal quantizer design under an incomplete statistical description of the source is first considered. It is assumed that a histogram of the source on a finite domain is known. The compandor model for a non-uniform quantizer with a large number of output levels is employed. Both minimum mean and minimaz error criteria are investigated leading to the design of piecewise linear compressors. Topics on the partitioning of the histogram are included. For vector quantization, the design of a spherical coordinates quantizer in k dimensions is discussed. Exact and compandor model solutions are derived as is the factorization of the quantization levels to each quantizer. Numerical examples are presented along with asymptotic results. Also investigated is the optimality of polar quantizers with the subsequent development of optimal circularly symmertric quantizers. Examples of these Dirichlet polar quantizers for the bivariate Gaussian source are included and their performance is compared to optimum error rates. The topic of implementation is considered. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1983
- Accession Number
- ADA127258
Entities
People
- John B. Thomas
- Peter F. Swaszek
Organizations
- Princeton University